Good question! Both Datafold and Atlan support data monitoring as a secondary feature, but have different main focuses:
Datafold is primarily known for their Data Diff regression testing that simulates the result of a PR on your data within a CI/CD workflow. There’s definitely a need for proactively preventing data issues from occurring in the first place, but issues introduced via code are only one subset of potential data quality issues.
Metaplane is focused on catching the symptoms first via continuous monitoring. Regression tests don’t replace the need for observability, and vice-versa.
Atlan is primarily known for their data workspace features that make collaboration easier, like a data dictionary, SQL editor, and governance.
Data collaboration is a huge unsolved problem and data monitoring does play a role there. But Metaplane is focused squarely on the problem of detecting data issues and giving you relevant metadata to prioritize and debug.
Datafold is primarily known for their Data Diff regression testing that simulates the result of a PR on your data within a CI/CD workflow. There’s definitely a need for proactively preventing data issues from occurring in the first place, but issues introduced via code are only one subset of potential data quality issues.
Metaplane is focused on catching the symptoms first via continuous monitoring. Regression tests don’t replace the need for observability, and vice-versa.
Atlan is primarily known for their data workspace features that make collaboration easier, like a data dictionary, SQL editor, and governance.
Data collaboration is a huge unsolved problem and data monitoring does play a role there. But Metaplane is focused squarely on the problem of detecting data issues and giving you relevant metadata to prioritize and debug.